Robert Tibshirani is a Professor in the Departments of Statistics and Health Research and Policy at Stanford University. He received a B.Math. from the University of Waterloo, an M.Sc. from the University of Toronto and a Ph.D. from Stanford University. He was a Professor at the University of Toronto from 1985 to 1998. In his work he has made important contributions to the analysis of complex datasets, most recently in genomics and proteomics. Some of his most well-known contributions are the lasso, which uses L1 penalization in regression and related problems, generalized additive models and Significance Analysis of Microarrays (SAM). He also co-authored four books "Generalized Additive Models", "An Introduction to the Bootstrap", and "The Elements of Statistical Learning" (now in its second edition) and "Statistical learning with Sparsity".